Many businesses utilize a computer server system (e.g., one or more computers) to provide a computer-implemented service to their customers. For example, some merchants may implement a website or a cloud-based application on the computer server system to provide a personalized service or a content distribution service (e.g., social networking, video streaming, cloud storage, etc.) directly to their customers. For another example, some merchants may utilize a website or a cloud-based application to sell their own or affiliated products. In these examples, the computer server system may execute a digital event profile filter to identify malicious actions occurring on the computer-implemented services, e.g., to detect fraudulent transactions, fraudulent usage, spamming across service accounts, etc. The computer server system may also execute a digital event profile filter to classify electronic transactions. For example, the computer-implemented services can utilize the digital event profile filter to identify a subset of all electronic transactions or potential electronic transactions to commit resources to (e.g., the computing or memory resources of the computer server system). The computer server system may also execute a digital event profile filter to estimate the likelihood of known outcome based on the digital event profile presented to the filter. For example, a digital event profile could be an electronic record of an individual's past driving records, claim history and model of the vehicle. The digital event profile filter can generate a score that estimate the risk of an individual involved in a car accident. The output of the digital profiler can then be used as an input for computing the insurance premium required for the individual.
The digital event profile filters enable objective data-driven analysis, such as an event classification analysis. An event classification analysis can be used to estimate outcomes of electronic transaction events based on quantifiable features (e.g., attributes, properties, factors and parameters) of the electronic transaction events. For example, the electronic transaction events can include processing an electronic transfer, presenting an electronic advertisement via a computer interface, or opening or closing a service account on the computer server system. The outcomes, for example, can be receiving a processing error, causing a user to purchase a product through the computer interface, causing a user to lodge a complaint, preventing a malicious activity, etc.
These quantifiable features can be measured and/or collected before, concurrently, or after the outcomes occur. In some cases, the estimation involves predicting an outcome that has yet to happen. An example may be predicting whether a marketing email will lead to a product sales. In other cases, the estimation involves uncovering an outcome without direct observation of the outcome, e.g., by analyzing observable features related to the event that produced the outcome. An example may be credit card or email fraud detection.
An electronic transaction event, which may include related sub-events, may be related to an unknown outcome from the perspective of a business entity. Let x (quantifiable features) be an m-dimensional vector (e.g., a total of m quantifiable features), where x∈ m represents all the available quantifiable features, including factors that can be measured or used to determine the outcome y of the electronic transaction event. For illustrative purposes, the outcome can be simplify as yi∈{−1,1} for each electronic transaction event. That is, the outcome results in either a positive outcome or a negative outcome for the business entity.
Often, business entities want to be able to focus on the event that has the highest return based on limited resources. A desirable outcome can be a positive one, such as generating a donation from direct mailing, or a negative one, such as fraud detection or the amount of insurance claim made in a car accident. It is also quite often in real-world problems that the set of events that will lead to the desirable outcome is a very small portion of all the events available or possible.